Abstract
       This article deals with research of the highly alumina materials ALKO 65 M, specifically with the refractory brick with the positions D 16. Three physical properties were studied: cold compression strength, volume weight, apparent porosity and the statistical dependence between them. The quality control charts describe the course of the values of the individual properties during the year 2001. Accounted were the most frequent reasons of the break of these refractory bricks.
       One of the features required by the efficiency evaluation of the quality control system according to EN ISO 9000 standards is application of statistical methods. As a part of production and products quality control are statistical methods applied also in metallurgy industry including refractory materials production. Present work deals with output control, when external defects and dimensional tolerances are tested.
       In case of high-alumina material ALKO 65M, at all positions, the statistical testing runs as follows: samples are taken from the top middle front part of every other waggon passing through the tunnel furnace. Subsequently, above-mentioned physical-chemical properties of the samples are measured.  Materials with high aluminium content have outstanding heat resistance. The most important  properties of high alumina materials in term of its application in metallurgy are mechanical and rheological properties at elevated temperatures, i.e. ability to withstand high temperature without chemical and mechanical failure, compression strength, compactness, abrasion resistance, deformation resistance and resistance to thermal shock as well as resistance to corrosion and erosion by high-temperature melts (metal and slag) and gases.
       Present work deals with the study of high-alumina refractory material ALKO 65M. Regular mass products, position D16 shaped pieces were selected as the object for this study. These are wedge shaped refractory bricks with dimensions 250x124x73/57 mm.
       Proper use of statistical methods serves for quick and efficient regressive evaluation of production process stability and final product quality, thus enabling application of effective corrective actions.